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English(EN) On Universality of Non-Separable Approximate Message Passing Algorithms

新框架探索不可分离 AMP 算法的普遍性

研究人员引入了一个新的框架来理解不可分离近似消息传递 (AMP) 算法的普遍性。这项工作识别出了一种张量的有界组合性质 (BCP),它使具有多项式非线性的 AMP 能够表现出适用于 i.i.d. 高斯项以外的矩阵的状态演化。该研究还为 Lipschitz AMP 算法实现类似通用保证的条件进行了形式化,证明了许多常见的不可分离非线性满足此标准。 AI

影响 为理解迭代学习算法提供了理论基础,可能影响未来人工智能模型的开发。

排序理由 关于理论算法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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新框架探索不可分离 AMP 算法的普遍性

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关于理论算法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Max Lovig, Tianhao Wang, Zhou Fan ·

    不可分离近似消息传递算法的普适性研究

    arXiv:2506.23010v2 Announce Type: replace-cross Abstract: Mean-field characterizations of first-order iterative algorithms -- including Approximate Message Passing (AMP), stochastic and proximal gradient descent, and Langevin diffusions -- have enabled a precise understanding of …